Learn to Think in Color

What Makes Workplace Feedback Actually Change Behavior? Why some comments fade by Monday—and others permanently reset the bar Framing the Question Effective workplace feedback isn’t about saying something “nice but honest”; it’s about creating conditions where people  actually  change what they do next week. Workplace feedback that changes behavior is specific, timely, and tied to a meaningful outcome, not a vague judgment or a personality critique. When you understand the psychology behind how adults learn at work, feedback becomes less about awkward conversations and more about tiny course corrections that compound over time. Below we’ll break down the ingredients of behavior-changing feedback, how to deliver it, and what it looks like in real teams. The Core Formula: Clear, Caring, Consequential Most feedback fails because it’s fuzzy (“great job”), feels like an attack (“you’re not strategic”), or lands in a vacuum (no clear stakes). Feedback that  actually  chang...

How Are Network Effects Impacted by Generative AI? When your flywheel meets a stochastic parrot with superpowers Big-picture framing Generative AI is reshaping  network effects and generative AI dynamics  at every layer: data, users, and products. In classic platforms, more users mean more value for each user; now, more users also mean more data, faster learning, and better models. The core question shifts from “How big is our network?” to “How quickly can we compound learning from our network?” Instead of replacing network effects, AI  bends and intensifies  them. It can turn weak flywheels into strong ones, transform single-sided products into ecosystems, and in some cases even erode old moats by lowering switching costs. If you build, invest in, or compete with AI products, understanding these new loops is now part of the job. Network effects 101 (in one minute) Classic  network effects : The product gets more valuable as more people use it. Each new user add...

Why do small physical changes cascade into large effects? The hidden rules that let tiny nudges trigger massive outcomes Big-picture framing We’re used to thinking in straight lines: small cause, small effect. But  small physical changes  often trigger surprisingly large consequences because many systems aren’t linear—they’re perched near thresholds, packed with feedback loops, and sensitive to timing. This piece unpacks why a tiny nudge can flip a system into a new state, how energy and stress quietly accumulate, and where amplification and damping hide in everyday structures, technologies, and natural environments. By the end, you’ll see not just why cascades happen, but also why they often  don’t —and how that shapes risk in the real world. The myth of “proportional response”: why small ≠ small We instinctively expect the world to behave like a dimmer switch: move it a little, the light changes a little. That holds in  linear systems , where output scales neatly w...

  Why are some people more annoying than others? It’s not just them — it’s also your brain, your boundaries, and the situation teaming up. Big Picture Why this question matters We all know a few people who feel instantly more annoying than others: the coworker who overshares, the neighbor who talks too loudly, the friend who always runs late. “Annoying people” are usually a mix of clashing expectations, habits that add friction, and your own state of mind. This piece explains why certain people trigger you, when annoyance is a real red flag (not just a pet peeve), and how to respond more intentionally instead of just simmering or avoiding them. Annoyance is a feature, not a bug Annoyance is your brain’s low-level alarm system. It pops up when a boundary is brushed, a norm is broken, or your attention is stretched too far. That talkative colleague or interrupting friend isn’t just “annoying”—they’re a signal that something in the interaction doesn’t match what you expected or can ha...